Towards privacy-anomaly detection: Discovering correlation between privacy and security-anomalies

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dc.contributor.author Khan, Muhammad Imran
dc.contributor.author Foley, Simon N.
dc.contributor.author O'Sullivan, Barry
dc.date.accessioned 2021-02-24T11:04:33Z
dc.date.available 2021-02-24T11:04:33Z
dc.date.issued 2020-08-06
dc.identifier.citation Khan, M. I., Foley, S. N. and O’Sullivan, B. (2020) 'Towards Privacy-anomaly Detection: Discovering Correlation between Privacy and Security-anomalies', Procedia Computer Science, 175, pp. 331-339. doi: 10.1016/j.procs.2020.07.048 en
dc.identifier.volume 175 en
dc.identifier.startpage 331 en
dc.identifier.endpage 339 en
dc.identifier.uri http://hdl.handle.net/10468/11103
dc.identifier.doi 10.1016/j.procs.2020.07.048 en
dc.description Part of special issue: The 17th International Conference on Mobile Systems and Pervasive Computing (MobiSPC), The 15th International Conference on Future Networks and Communications (FNC),The 10th International Conference on Sustainable Energy Information Technology en
dc.description.abstract In this paper a notion of privacy-anomaly detection is presented where normative privacy is modelled using k-anonymity. Based on the model, normative privacy-profiles are constructed, and deviation from normative privacy-profile at runtime is labelled as a privacy-anomaly. Furthermore, the paper investigates whether there is a correlation between security-anomalies and privacy-anomalies, that is, whether the privacy-anomalies labelled by privacy-anomaly detection system are detected by conventional security-anomaly detection system used for detecting malicious accesses to databases by insiders. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Elsevier en
dc.relation.uri https://www.sciencedirect.com/science/article/pii/S1877050920317294
dc.rights © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) en
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ en
dc.subject Anomaly detection en
dc.subject Anonymization en
dc.subject Electronic privacy en
dc.subject K-anonymity en
dc.subject Relational databases en
dc.title Towards privacy-anomaly detection: Discovering correlation between privacy and security-anomalies en
dc.type Article (peer-reviewed) en
dc.type Conference item en
dc.internal.authorcontactother Barry O'Sullivan, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: b.osullivan@cs.ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2021-02-24T10:58:01Z
dc.description.version Published Version en
dc.internal.rssid 556366643
dc.contributor.funder Science Foundation Ireland en
dc.contributor.funder European Regional Development Fund en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Procedia Computer Science en
dc.internal.copyrightchecked Yes
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Leuven, Belgium en
dc.internal.IRISemailaddress b.osullivan@cs.ucc.ie en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/ en


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© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) Except where otherwise noted, this item's license is described as © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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